AI Assistant Implementation for Actuator Manufacturing Company

Phase 1. Internal Co-Pilot Deployment (4 Months)

• Plan and validate the AI assistant’s capabilities in a controlled, internal environment.

• Data Preparation : Collect and structure 2 years of historical customer interaction data, including past conversation logs, support tickets, product manuals, FAQs, and technical PDFs.
• Training : Train the AI on industry-specific terminology, common customer queries, and product details from manuals and technical documents.
• Initial Integration :

• Integrate the assistant with HubSpot CRM for ticket generation and tracking customer interactions.
• Integrate with SAP S/4HANA ERP for real-time spare parts and order tracking.

• Conduct red-team testing to identify potential vulnerabilities, including hallucination testing for AI-generated responses to ensure no sensitive information leakage.
• Co-Pilot Deployment : Deploy the assistant as a co-pilot for customer support agents to help them retrieve accurate responses in real-time, referencing documents like FAQs and product manuals.

• Outcome :

• Agent efficiency improved by 30% through faster response support.
• Internal testing enhanced intent recognition, troubleshooting, and integration with manuals and FAQs.

Phase 2. Fine-Tuning & Optimization (2 Months)

• Improve the AI’s performance based on real-time data and refine its capabilities.

• Data Analysis : Analyze real-time customer-agent interactions and feedback to improve the AI’s ability to handle complex queries. Additional product manuals, FAQs, and knowledge articles are continuously added to the dataset.
• Training Updates :

• Fine-tune the assistant to handle slang, typos, and nuanced queries, improving its ability to process informal language.
• Expand its capability to provide more personalized recommendations by training it on customer profiles and past interaction history.

• Quality Assurance : Perform extensive quality assurance and stress testing to ensure smooth integration with HubSpot CRM and SAP S/4HANA ERP, ensuring the assistant can access and reference relevant documents (FAQs, PDFs) in real-time.
• Implement a comprehensive enablement program to re-train customer support agents on the AI assistant’s functionalities and provide them with tools to smoothly transition to the new system.

• Outcome :

• The assistant achieved 85%+ intent accuracy using text lookup and semantic vector matching, cutting response times to under 30 seconds.
• Improved access to manuals and FAQs enabled better handling of complex queries and personalized support.

Phase 3. External Deployment (5 Months)

• Expand the use of the AI assistant to external customers, making it publicly accessible.

• Wider Deployment : Deploy the assistant across the company’s support channels (website, mobile app, and service portals) to engage with customers directly.
• Establish an escalation SLA to ensure critical queries are promptly transferred to human agents when necessary, maintaining customer satisfaction and service continuity.
• Enhanced CRM & ERP Integration : Ensure seamless integration with HubSpot CRM for automated ticket generation and real-time customer feedback collection, and SAP S/4HANA ERP for live product ordering, warranty processing, and spare parts tracking.
• Data Utilization :

• Ensure the assistant can pull data from knowledge bases, including manuals, PDFs, and FAQs, to resolve customer issues and provide real-time information.
• Train the assistant to offer personalized warranty processing, spare parts ordering, and live order tracking, leveraging product manuals and specifications.

• Outcome :

• The assistant autonomously handled 48% of support queries, easing call center load and boosting efficiency.
• Real-time access to manuals, FAQs, and warranty info enabled faster resolutions and improved customer satisfaction.